Fix CNN v2 static feature channel mapping (p4-p7 → channels 8-11)

Fixed bug in gen_identity_weights.py --p47 mode: static features p4-p7
(uv_x, uv_y, sin20_y, bias) are at input channels 8-11, not 4-7.

Weight tensor layout:
- Channels 0-3: Previous layer output (4D RGBA)
- Channels 4-11: Static features (8D: p0-p7)

Static features:
- p0-p3 (channels 4-7): RGB+D from mip level
- p4-p7 (channels 8-11): uv_x, uv_y, sin20_y, bias

Updated:
- training/gen_identity_weights.py: Change weights[i,i+4] to weights[i,i+8]
- workspaces/main/weights/mix_p47.bin: Regenerated (not in repo)
- doc/CNN_V2.md: Add Input Channel Mapping section with full layout table

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

1 files changed, 9 insertions, 4 deletions

diff --git a/training/gen_identity_weights.py b/training/gen_identity_weights.py
index 5756e67..5d83bfb 100755
--- a/training/gen_identity_weights.py
+++ b/training/gen_identity_weights.py
@@ -7,8 +7,8 @@ Output Ch{0,1,2,3} = Input Ch{0,1,2,3} (ignores static features).
 With --mix: Output Ch{i} = 0.5*Input Ch{i} + 0.5*Input Ch{i+4}
   (50-50 blend, avoids overflow)
 
-With --p47: Output Ch{i} = Input Ch{i+4} (static features only)
-  (p4→ch0, p5→ch1, p6→ch2, p7→ch3)
+With --p47: Output Ch{i} = static p{4+i} (uv_x, uv_y, sin20_y, bias)
+  (p4/uv_x→ch0, p5/uv_y→ch1, p6/sin20_y→ch2, p7/bias→ch3)
 
 Usage:
   ./training/gen_identity_weights.py [output.bin]
@@ -26,7 +26,10 @@ def generate_identity_weights(output_path, kernel_size=1, mip_level=0, mix=False
     """Generate identity weights: output = input (ignores static features).
 
     If mix=True, 50-50 blend: 0.5*p0+0.5*p4, 0.5*p1+0.5*p5, etc (avoids overflow).
-    If p47=True, transfers p4→p0, p5→p1, p6→p2, p7→p3 (static features only).
+    If p47=True, transfers static p4-p7 (uv_x, uv_y, sin20_y, bias) to output channels.
+
+    Input channel layout: [0-3: prev layer, 4-11: static (p0-p7)]
+    Static features: p0-p3 (RGB+D), p4 (uv_x), p5 (uv_y), p6 (sin20_y), p7 (bias)
 
     Binary format:
       Header (20 bytes):
@@ -61,8 +64,10 @@ def generate_identity_weights(output_path, kernel_size=1, mip_level=0, mix=False
 
     if p47:
         # p47 mode: p4→ch0, p5→ch1, p6→ch2, p7→ch3 (static features only)
+        # Input channels: [0-3: prev layer, 4-11: static features (p0-p7)]
+        # p4-p7 are at input channels 8-11
         for i in range(out_channels):
-            weights[i, i + 4, center, center] = 1.0
+            weights[i, i + 8, center, center] = 1.0
     elif mix:
         # Mix mode: 50-50 blend to avoid overflow
         for i in range(out_channels):